The present system is directed to a morphological processing system for skeletonizing a binary image and detecting distinctive features therein. In particular, the system is designed for use in detecting defects in circuit patterns.
Various efforts have been made to develop algorithms for thinning or skeletonizing binary images. One such prior effort is disclosed in an article entitled "A Fast Parellel Algorithm for Thinning Digital Patterns" which was published in Communications of the ACM, Vol. 27, No. 3, March, 1984 by the authors T. Y. Zhang and C. Y. Suen. The Zhang and Suen algorithm analyzes the images in 3.times.3 matrices. The algorithm requires two iterations, one aimed at deleting the southeast boundary points and the northwest corner points while the other is aimed at deleting the northwest boundary points and the southeast corner points. Another such effort at thinning is disclosed in U.S. Pat. No. 4,949,390 (Iverson et al.). Iverson et al. discloses a single pass thinning and trimming algorithm which reviews 4.times.5 pixel neighborhood images.
Automatic optical inspection systems have been developed which make use of thinning algorithms to simplify the task of feature detection in a printed circuit image. For example, U.S. Pat. No. 4,853,967 (Mandeville) discloses a system which seeks to detect such features as T-joints, blob-joints and terminal ends. Mandeville intersperses the use of thinning and comparing identified features with a design list.
It is an object of the present invention to provide an improved single pass thinning algorithm and apparatus for use in feature detection. It is thus a further object to provide an improved feature detection and reporting system.